A New Family of Polak-Ribiere-Polyak Conjugate Gradient Method with the Strong-Wolfe Line Search

被引：0
|
作者：
Ghani, Nur Hamizah Abdul [1 ]
Mamat, Mustafa [1 ]
Rivaie, Mohd [2 ]
机构：
[1] Univ Sultan Zainal Abidin UniSZA, Fac Informat & Comp, Kuala Terengganu 21300, Terengganu, Malaysia
[2] Univ Teknol Mara UiTM, Dept Comp Sci & Math, Kuala Terengganu 21080, Terengganu, Malaysia
来源：
PROCEEDINGS OF THE 24TH NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES (SKSM24): MATHEMATICAL SCIENCES EXPLORATION FOR THE UNIVERSAL PRESERVATION | 2017年 / 1870卷
关键词：
SUFFICIENT DESCENT CONDITION; CONVERGENCE PROPERTIES; GLOBAL CONVERGENCE; MINIMIZATION; COEFFICIENTS; PROPERTY; PROOF;
D O I：
10.1063/1.4995892
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Conjugate gradient (CG) method is an important technique in unconstrained optimization, due to its effectiveness and low memory requirements. The focus of this paper is to introduce a new CG method for solving large scale unconstrained optimization. Theoretical proofs show that the new method fulfills sufficient descent condition if strong Wolfe-Powell inexact line search is used. Besides, computational results show that our proposed method outperforms to other existing CG methods.
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页数：8
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